用于电磁振动采集的快速制造多材料悬臂

IF 4.3 2区 综合性期刊 Q1 ENGINEERING, ELECTRICAL & ELECTRONIC
Philipp Gawron;Thomas M. Wendt;Stefan J. Rupitsch
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摘要

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Additively Manufactured Multimaterial Cantilever for Electromagnetic Vibration Harvesting
This study presents a novel, additively manufactured, multimaterial vibration harvester that employs fused filament fabrication (FFF) and wire embedding. The device features a clamped-free cantilever design. We investigate the effects of the embedding height of the coil layer and the coil’s displacement within the layer on the cantilever’s eigenfrequency. These parameters enable tuning of the cantilever’s first resonance frequency within a range of 27 Hz without altering its dimensions. In addition, the embedded wire serves as a coil for energy harvesting. We determined the electrical power output under mechanical excitations of up to 3 g. Piezo jetting (PJ) is also explored as an alternative printing technique to fabricate a double-sided coil structure on the cantilever. Both printing techniques are discussed in detail.
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来源期刊
IEEE Sensors Journal
IEEE Sensors Journal 工程技术-工程:电子与电气
CiteScore
7.70
自引率
14.00%
发文量
2058
审稿时长
5.2 months
期刊介绍: The fields of interest of the IEEE Sensors Journal are the theory, design , fabrication, manufacturing and applications of devices for sensing and transducing physical, chemical and biological phenomena, with emphasis on the electronics and physics aspect of sensors and integrated sensors-actuators. IEEE Sensors Journal deals with the following: -Sensor Phenomenology, Modelling, and Evaluation -Sensor Materials, Processing, and Fabrication -Chemical and Gas Sensors -Microfluidics and Biosensors -Optical Sensors -Physical Sensors: Temperature, Mechanical, Magnetic, and others -Acoustic and Ultrasonic Sensors -Sensor Packaging -Sensor Networks -Sensor Applications -Sensor Systems: Signals, Processing, and Interfaces -Actuators and Sensor Power Systems -Sensor Signal Processing for high precision and stability (amplification, filtering, linearization, modulation/demodulation) and under harsh conditions (EMC, radiation, humidity, temperature); energy consumption/harvesting -Sensor Data Processing (soft computing with sensor data, e.g., pattern recognition, machine learning, evolutionary computation; sensor data fusion, processing of wave e.g., electromagnetic and acoustic; and non-wave, e.g., chemical, gravity, particle, thermal, radiative and non-radiative sensor data, detection, estimation and classification based on sensor data) -Sensors in Industrial Practice
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